/***************************************************************************
 *   Copyright (C) 2010 by Oleg Goncharov  *
 *   $EMAIL$                           *                          
 *                                                                         *
 *   This file is part of ChessVision.                                     *
 *                                                                         *
 *   ChessVision is free software; you can redistribute it and/or modify   *
 *   it under the terms of the GNU General Public License as published by  *
 *   the Free Software Foundation; either version 2 of the License, or     *
 *   (at your option) any later version.                                   *
 *                                                                         *
 *   This program is distributed in the hope that it will be useful,       *
 *   but WITHOUT ANY WARRANTY; without even the implied warranty of        *
 *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the         *
 *   GNU General Public License for more details.                          *
 *                                                                         *
 *   You should have received a copy of the GNU General Public License     *
 *   along with this program; if not, write to the                         *
 *   Free Software Foundation, Inc.,                                       *
 *   59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.             *
 ***************************************************************************/
#include "ckmeanfigure.h"

namespace Chess {

//TODO This constructor does not perform full initialization.
CFigureKMean::CFigureKMean(const std::string& config, ClassModel model, int _k, int history_length) : 
	CFigureMultiClass(config, model, history_length), k(_k)
{
}

void CFigureKMean::Train(CvMat examples, CvMat classes, CvMat examples_idx) {
	classifier.train(&examples, &classes, &examples_idx, false, 32);
}


bool CFigureKMean::Classify(CvMat board, CvMat classes) {
	classifier.find_nearest(&board, k, &classes);
	return true;
}

}

